Abstract

Using spectral analysis of vibration to predict the presence of defects in the bearings of low-speed machines can be difficult. The vibrations generated by these machines are of low amplitude compared with the level of electrical noise, and in many cases this prevents the detection of defects in the bearings. In this paper, we used some real-world historical cases from the pulp and paper industries to illustrate that with an integrated analysis of the vibration spectrum and waveform, and the use of averages and a fine frequency resolution, it is possible to detect defects in bearings of low-speed machines. A practical example showing the application of the demodulation technique on a roll of the third press of a paper machine is also presented.